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  • About Brain Code Camp

General Information

  • Schedule
  • On-Site Meetups
  • Staff
  • Office Hour Teams
  • Datasets
  • Graduation Requirements
  • Frequently Asked Questions

Prerequisites

  • Brain Building Blocks
    • Welcome to the Brain!
      • Hello, Brains!
      • Essential Neuroanatomy
      • Functional Area & Network
      • Language of the Brain
    • Neuroscience Methods
      • Introduction to Brain Science Toolbox
      • The Era of Localization
      • Measuring the Immeasurable
      • Sneak Peek Inside the Blackbox
      • Journey Into the Brain
    • Brain & Behaviors
      • Connecting Brain & Behavior
      • Single Neuron Studies
      • EEG Studies
      • fMRI Studies
    • Brain Signals
      • Solve the Brain Signal
      • Neural Firing
      • EEG Signal
      • fMRI Signal
    • Models of the Mind
      • Topographic Organization
      • Biological Neuron
      • Neural and Population Tuning
      • Neural Representation
      • How Does The Brain Decide?
    • Data Modeling
      • Data Handling and Exploration
      • Goals of Modeling
      • Types of Modeling
      • Model Evaluation
    • Neuro & AI
      • Artificial Intelligence & Biological Intelligence
      • Artificial Intelligence & Biological Intelligence II
      • Supervised Deep Learning
      • Reinforcement Learning
      • Unsupervised Learning
      • Language Models
    • Medical Applications
      • Diagnosis and Monitoring
      • Computational Neuropsychiatry
    • Social Applications
      • Brain Computer Interface
  • From BBB to BCC
    • Data Visualization
    • Modeling
  • Intro to Modeling and Model Selection
    • Welcome to Intro to Modeling and Model Selection
    • Simple Linear Model
    • Polynomial Regression, Overfitting, and Regularization
    • Training, Validation and Test Data
    • Outro

Dimensionality Reduction (Week 1)

  • Intro to Dimensionality Reduction
  • The Basics
  • Principal Component Analysis (PCA)
  • Applying PCA to CDT Images
  • Nonlinear Methods
  • Outro

Machine Learning (Weeks 2-3)

  • ML Part 1 (Week 2)
    • Introduction to Machine Learning
    • Logistic Regression
    • Support Vector Machine (SVM)
  • ML Part 2 (Week 3)
    • Decision Tree and Random Forest
    • k-Nearest Neighbors (k-NN)
    • Outro

Deep Learning (Week 4)

  • Intro to Deep Learning
  • Fundamentals of Deep Learning
  • Introduction to Pytorch
  • Concentration Prediction with EEG
  • Classification with Convolutional Neural Network Using PyTorch
  • Outro

Signal Processing (Week 5)

  • Intro to Signal Processing
  • Sampling and Signal Averaging
  • Discrete Fourier Transform (DFT)
  • Short Time Fourier Transform (STFT)
  • Audio Example
  • Outro

Modality Exploration (Weeks 6-8)

  • EEG
    • EEG Preprocessing and Analysis
  • fMRI
    • Introduction to fMRI Preprocessing
  • Spiking Data
    • Spiking Data Processing and Analysis

Applications (Weeks 9-13)

  • Applying What You Have Learned to Your Project

Extra Lectures

  • Recurrent Neural Network
  • Attention Mechanisms and Transformer
  • Graph Neural Network
  • Reinforcement Learning
  • Statistics
  • Dimensionality Reduction

Extra Coding

  • Hands-On Deep Learning with Pytorch
  • Object Detection with Transformer
  • Breast Cancer Segmentation Using Transformers
  • Image Classification

Previous Offerings

  • 2024
    • Graduates
    • Projects
    • Activities
  • 2023
    • Graduates
    • Projects
    • Activities

Index

R

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  • RFC
    • RFC 2616, [1]
    • RFC 5322, [1]

By Brain Code Camp Community

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